Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
About this Course
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- 4 stars26.14%
- 3 stars6.24%
- 2 stars1.60%
- 1 star0.90%
TOP REVIEWS FROM BUILDING BATCH DATA PIPELINES ON GOOGLE CLOUD
A great course to help understand the various wonderful options Google Cloud has to offer to move on-premise Hadoop workload to Google Cloud Platform to leverage scalability of clusters.
This course includes new services not much mentioned in the previous course. But, proportion of the module is not balanced.
Good introduction to pipelines building in GCP, Starting labs need to be in more detail. Other than that very good course.
The pipeline building portion assumes in part that the learner has previous experience with programming. Further break down of the Python pipeline builds would be helpful.
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